Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Assamese
wav2vec2
mozilla-foundation/common_voice_8_0
Generated from Trainer
robust-speech-event
model_for_talk
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use DrishtiSharma/wav2vec2-large-xls-r-300m-as-v9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DrishtiSharma/wav2vec2-large-xls-r-300m-as-v9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DrishtiSharma/wav2vec2-large-xls-r-300m-as-v9")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("DrishtiSharma/wav2vec2-large-xls-r-300m-as-v9") model = AutoModelForCTC.from_pretrained("DrishtiSharma/wav2vec2-large-xls-r-300m-as-v9") - Notebooks
- Google Colab
- Kaggle
| {"ঁ": 1, "ং": 2, "ঃ": 3, "অ": 4, "আ": 5, "ই": 6, "ঈ": 7, "উ": 8, "এ": 9, "ঐ": 10, "ও": 11, "ঔ": 12, "ক": 13, "খ": 14, "গ": 15, "ঘ": 16, "ঙ": 17, "চ": 18, "ছ": 19, "জ": 20, "ঝ": 21, "ঞ": 22, "ট": 23, "ঠ": 24, "ড": 25, "ঢ": 26, "ণ": 27, "ত": 28, "থ": 29, "দ": 30, "ধ": 31, "ন": 32, "প": 33, "ফ": 34, "ব": 35, "ভ": 36, "ম": 37, "য": 38, "র": 39, "ল": 40, "শ": 41, "ষ": 42, "স": 43, "হ": 44, "়": 45, "া": 46, "ি": 47, "ী": 48, "ু": 49, "ূ": 50, "ৃ": 51, "ে": 52, "ৈ": 53, "ো": 54, "ৌ": 55, "্": 56, "ৎ": 57, "ড়": 58, "ঢ়": 59, "য়": 60, "ৰ": 61, "ৱ": 62, "|": 0, "[UNK]": 63, "[PAD]": 64} |